A geologic model is a computer-based representation of a subsurface earth volume, such as a petroleum reservoir or a depositional basin. In the oil and gas industry, geologic models are commonly used in activities such as determining the locations of wells, estimating hydrocarbon reserves, or planning reservoir-development strategies. Geologic models are also input to fluid flow simulations to test development and production scenarios in order to optimize return on investment. A key parameter in flow simulation is the spatial distribution of permeability, which together with the properties of the hydrocarbons and other fluid found in the subsurface reservoir, determines the producibility of the reservoir. Typically, the input data for geologic models includes data obtained through seismic prospecting techniques.
Seismic prospecting techniques are commonly used to aid in the search for and evaluation of subterranean hydrocarbon reservoirs. A seismic prospecting operation consists of three separate stages: data acquisition, data processing, and data interpretation. The success of the operation depends on satisfactory completion of all three stages.
In the data acquisition stage, a seismic source is used to generate an acoustic signal that propagates into the earth and is at least partially reflected by subsurface seismic reflectors. The reflected signals are detected and recorded by an array of seismic receivers located at or near the surface of the earth, in an overlying body of water, or at known depths in boreholes.
During the data processing stage, the recorded seismic signals are refined and enhanced using a variety of procedures that depend on the nature of the geologic structure being investigated and on the characteristics of the raw data. In general, the purpose of the data processing stage is to produce an image of the subsurface from the recorded seismic data for use during the data interpretation stage.
The purpose of the data interpretation stage is to determine information about the subsurface geology of the earth from the processed seismic data. The results of the data interpretation stage may be used to determine the general geologic structure of a subsurface region, or to locate potential hydrocarbon reservoirs, or to guide the development of an already discovered reservoir.
At present, the conclusions, which can be made after the data interpretation stage, are generally limited to broad descriptions of the size and general nature of subsurface structures due to the limited resolution of seismic data. The descriptions may for example provide an indication of the total volume of hydrocarbons, which might be retained in such structures. However, present technology does not allow the analyst to determine production rates from the subsurface formations if hydrocarbons are discovered. In addition, when an exploration well has been drilled, present technology does not allow an analyst to be able to accurately characterize the nature of the subsurface internal geometry in locations other than in the most immediate region of any such well. In particular, reservoir permeability and continuity are not well characterized by present technology.
The hydrocarbon volume and rate of production depend on a variety of factors, including fluid properties, reservoir net-to-gross, porosity, permeability, spatial variability in grain size distribution, and connectivity. Reservoir connectivity, a measure of the communication (or lack thereof) between points within the reservoir, is a strong function of the reservoir internal geometry and is commonly a primary factor controlling hydrocarbon production efficiency and ultimate recovery. There is a need to predict the detailed internal geometry of subsurface reservoirs using geologic data, such as seismic data, and without having to drill many exploration and delineation wells. Such a capability would facilitate estimation of hydrocarbon volume in place and production rates early in the hydrocarbon exploration and development process.
Another step in geologic modeling is “gridding.” Gridding is the division of the subsurface region into cells, within which the rock properties are regarded as uniform. The ability to accurately model reservoir internal geometry and connectivity is largely dependent on the vertical grids used in the modeling processes due to the nature of stratification and vertical heterogeneity in the reservoir. As a result, the gridding methods in geologic modeling focus mainly on the vertical variation of attributes of a geologic model. In map view, uniform rectangular grids are commonly used for relatively small variations of attributes in the lateral directions.
There are four gridding methods commonly used in commercially available geologic modeling tools. Examples of commercially available geologic modeling tools include: SGM (Landmark Graphics Corporation, Stratamodel Geocellular Modeling (SGM), 1989-2003), RMS (Roxar ASA, Irap RMS (Reservoir Modeling Systems), 1993-2003), gOcad (Earth Decision Sciences Corporation, gOcad, 1989-2003), and Petrel (Technoguide (A Schlumberger Product Group), Petrel™ Workflow Tools, 1996-2003). The four gridding methods used in the petroleum industry are commonly named proportional, onlap, truncation, and reference. The name of each method can vary from one tool to another. For example, “reference-grid” in RMS is the same as “depositional-grid” in SGM. The choice of the most appropriate gridding method to use when building a geologic model depends on the geologic modeler's experience and personal judgement of the model's particular geologic setting. Gridding style, however, was created to mimic natural patterns of erosion and deposition observed in nature at the seismic scale.
The gridding methods used in the most commercially available geologic modeling tools (such as, SGM, RMS, gOcad, and Petrel) are based on methods disclosed in two of Swanson's patents. The patents are U.S. Pat. Nos. 4,821,164 and 4,991,095.
FIG. 1(a) is a cross-section illustration of stratification of sand bodies 1, 2, 3, 4 and 5 and low permeability layers 6. FIGS. 1(b), 1(c), 1(d), and 1(e) illustrate sand bodies 1, 2, 3, 4, and 5 and low permeability layers 6 from FIG. 1(a) using conventional grids.
As shown in FIG. 1(b), “Proportional-grid” assumes that the reservoir sand bodies 1, 2, 3, 4, and 5 within the given sequence are parallel to the top 7 and basal surfaces 9 of the sequence 11. Therefore, the sequence is subdivided into the cells 13 proportional to the thickness of the sequence 11.
As shown in FIG. 1(c), “Onlap-grid” assumes that the sand bodies 1, 2, 3, 4, and 5 are parallel to the top surface 7 of the sequence 11. The sequence 11 is gridded with the constant thickness cells 13 that are parallel to the top surface 7 and may be truncated 15 by the basal surface 9 of the sequence 11.
As shown in FIG. 1(d), “Truncation-grid” assumes that the sand bodies 1, 2, 3, 4, and 5 are parallel to the basal surface 9 of the sequence 11. The sequence 11 is gridded with the constant thickness cells 13 that are parallel to the basal surface 9 and may be truncated 15 by the top surface 7 of the sequence 11.
As shown in FIG. 1(e), “Reference-grid” assumes that the sand bodies 1, 2, 3, 4, and 5 are parallel to a given surface (or reference surface) 17, such that the constant thickness cells 13 are constructed parallel to the reference surface 17 and may be truncated 15 by the top 7 and basal surfaces 9 of the sequence 11. The reference surface 17 is usually some sort of geologic datum. In this figure, the reference surface is the bottom of sand body 2.
The problem is that none of these gridding methods represent the true internal geometry accurately. To illustrate this problem, there are five disconnected sand bodies 1, 2, 3, 4, and 5 within the sequence 11 of FIG. 1(a) and the above gridding methods create significantly distorted representations as shown in FIGS. 1(b), 1(c), 1(d), and 1(e) when compared to FIG. 1(a). Sand body 1 is incorrectly connected with sand body 2 in the proportional-grids and onlap-grids as illustrated in FIGS. 1(b) and 1(c) respectively. As shown in FIG. 1(c), sand body 2 is incorrectly connected with sand body 3 in the onlap-grids. Furthermore, sand body 4 is incorrectly connected with sand body 5 in the truncation-grids of FIG. 1(d).
Some sand bodies are incorrectly disconnected within themselves. For example, sand body 4 is disconnected in the proportional-grids of FIG. 1(b) and sand body 2 is disconnected in the onlap-grids of FIG. 1(c). Furthermore, some sand bodies are erroneously disconnected from the fluid flow since some cells in these sand bodies only contact their neighbor cells at the corners, without face connections. For example, sand body 2 is disconnected in the proportional-grids of FIG. 1(b) and sand body 4 is disconnected in all of the four gridding methods as shown in FIGS. 1(b), 1(c), 1(d), and 1(e). Misalignment between the sand bodies and grids is the direct cause of this distortion problem.
The grids constructed by the above-mentioned prior art methods do not properly align themselves with the reservoir internal geometry. The alignment between the grids and the reservoir internal geometry is important for two reasons. First, any lack of alignment distorts the reservoir connectivity in the geologic model subsequently built. Second, when the geologic model is scaled up for reservoir performance simulation with coarser grids, the coarser grids will magnify the misrepresentations and distortions that exist in the geologic model. Consequently, the accuracy of any reservoir performance prediction will decrease, which will hamper reservoir management.
A reliable reservoir performance simulation depends strongly on the ability of a geologic model to accurately characterize the spatial distribution of permeability. Most important are the permeability extremes, such as high-permeability sand bodies and no-flow shale barriers, because the permeability extremes typically control the oil, gas, and water flows. The ability to model permeability is currently severely limited by the commercially available geologic model gridding methods. One reason that the existing geologic modeling tools have to adopt arbitrary lateral grid surfaces is that the actual strata geometry (or layering) of the sand objects is not known a priori. As a consequence, the reservoir connectivity is typically misrepresented in geologic models and the resulting performance simulation models. Accordingly, there is a need for a method that generates grids that follow the geometry of sand bodies and shale barriers. Preferably, these grids would allow the reservoir connectivity to be accurately characterized in a geologic model and preserved during upscaling for reservoir performance simulation. The current invention addresses the need by generating the lateral grid surfaces naturally, following the complex depositional and erosional processes observed in nature.